O reforço das competências de gestão nas instituições públicas: governança e gestão no poder legislativo municipal: estudo de caso na Câmara Municipal de Niterói

This thesis analyzes the governance in public institutions management, taking the Niteroi's Cityzenship Council as the reasearch object. In order to accomplish this goal, this thesis has been split into two parts. The first one introduces the discussion about management, manager's action and administration, differentiating the private approach from the public one. The characteristics of the public service and its models were defined, as they were incorporated in the last decades in parallel with the institutionalism and governance theories. In the second part a description is presented on the Brazilian's politician space construction, with emphasis in the cities and in the functioning of the public institutions according to the reality of the Brazilian's partisan system. The concept of accountability and the relation between repuplican powers were also discussed, followed by a case study. The analyses show the reality of the governance at the chamber of the councilmen of Niteroi in accordance with the methodology chosen to accomplishment the research. The conclusion points out the findings that were obtained during the research.

Comparação entre o ensino tradicional e o ensino tradicional com reforço por módulos, com ênfase na possível influência de valores e características sócio-econômicas no rendimento escolar

O objetivo deste trabalho foi analisar a utilização do ensino por módulos, utilizado como reforço de ensino, em Física e em Matemática, por alunos da lª série (2ºgrau) da Rede de Ensino Estadual do Rio de Janeiro. Pretendeu-se avaliar a utilização dessa metodologia a nível de rendimento dos alunos, e, também, relacioná-la à cosmovisão (tratada em termos de níveis de consciência, segundo Reich - 1970) e à situação sócio-econômica desses alunos (segundo escala de Guidi e Duarte, 1969).O estudo teve caráterexperimental, sendo constituídos grupos experimentais e de controle em quatro colégios estaduais dos municípios de Valença, Friburgo e Rio de Janeiro. Foram aplicados os seguintes instrumentos: a) testes diagnóstico e pós-testes, em Física e em Matemática, aos dois grupos de cada colégio; b) escalas destinadas a classificação dos alunos dos grupos experimentais em níveis de consciência e em classes sociais. Pretendeu-se estabelecer relação entre o rendimento obtido em Física e em Matemática e: a) metodologia utilizada; b) níveis de consciência apresentados pelos alunos; c) classificação sócio-econômica desses alunos. Os resultados obtidos evidenciaram que: 1) o rendimento obtido pelos alunos dos grupos experimentais de cada colégio, separadamente, nem sempre foi favorável; contudo, se considerados globalmente, esses mesmos resultados revelaram-se favoráveis aos grupos experimentais; 2) predodominou, em todos os colégios, o nível de Consciência III, seguido pelos níveis II e I (nesta ordem); 3) o rendimento obtido em Física pelos grupos experimentais correspondeu, em ordem decrescente, aos níveis de Consciência II, I e III (nesta ordem), constatando-se variação significativa entre as médias obtidas e o nível de consciência apresentado; 4) o rendimento obtido em Matemática pelos grupos experimentais correspondeu, em ordem decrescente, aos níveis de Consciênda lI, III e I, sem que se constatasse variação significativa entre as médias obtidas, conforme o nível de consciência apresentado; 5) predominaram, em todos os colégios, as classes sócio-econômicas baixa-superior e média-inferior, com incidência mínima da classe média-superior e exclusão das classes baixa e alta; 6) o rendimento obtido em Física pelos grupos experimentais não revelou variação significativa conforme a classe social dos alunos, embora as médias se elevassem em correspondência à elevação da classificaçãc sócio-econômica; 7) o rendimento obtido em Matemática pelos grupos experimentais acusou as médias mais altas nos alunos de nível sócio-econômico mais elevado, não se constatando aumento gradativo das médias, conforme o nível sócio-econômico dos alunos, nem variação significativa entre os resultados obtidos pelos alunos dos diferentes níveis sócio-econômicos. Concluiu-se pela validade da aplicação do reforço de ensino por módulos, em condições semelhantes e a clientelas semelhantes às consideradas no estudo.

Caracterização de atapulgita visando aplicação para reforço de materiais poloméricos

The clay mineral attapulgite is a group of hormitas, which has its structures formed by microchannels, which give superior technological properties classified the industrial clays, clays of this group has a very versatile range of applications, ranging from the drilling fluid for wells oil has applications in the pharmaceutical industry. Such properties can be improved by activating acid and / or thermal activation. The attapulgite when activated can improve by up to 5-8 times some of its properties. The clay was characterized by X-ray diffraction, fluorescence, thermogravimetric analysis, differential thermal analysis, scanning electron microscopy and transmission electron microscopy before and after chemical activation. It can be seen through the results the efficiency of chemical treatment, which modified the clay without damaging its structure, as well as production of polymer matrix composites with particles dispersed atapugita

Estudo da sinterabilidade de ligas de níquel obtidas por meio dos portadores de liga sic, si3n4 ou si metálico com grafita

Nickel alloys are frequently used in applications that require resistance at high temperatures associated with resistance to corrosion. Alloys of Ni-Si-C can be obtained by means of powder metallurgy in which powder mixtures are made of metallic nickel powders with additions of various alloying carriers for such were used in this study SiC, Si3N4 or Si metal with graphite. Carbonyl Ni powder with mean particle size of 11 mM were mixed with 3 wt% of SiC powders with an average particle size of 15, 30 and 50 μm and further samples were obtained containing 4 to 5% by mass of SiC with average particle size of 15 μm. Samples were also obtained by varying the carrier alloy, these being Si3N4 powder with graphite, with average particle size of 1.5 and 5 μm, respectively. As a metallic Si graphite with average particle size of 12.5 and 5 μm, respectively. The reference material used was nickel carbonyl sintered without adding carriers. Microstructural characterization of the alloys was made by optical microscopy and scanning electron microscopy with semi-quantitative chemical analysis. We determined the densities of the samples and measurement of microhardness. We studied the dissociation of carriers alloy after sintering at 1200 ° C for 60 minutes. Was evaluated also in the same sintering conditions, the influence of the variation of average particle size of the SiC carrier to the proportion of 3% by mass. Finally, we studied the influence of variation of the temperatures of sintering at 950, 1080 and 1200 ° C without landing and also with heights of 30, 60, 120 and 240 minutes for sintering where the temperature was 950 °C. Dilatometry curves showed that the SiC sintered Ni favors more effectively than other carriers alloy analyzed. SiC with average particle size of 15 μm active sintering the alloy more effectively than other SiC used. However, with the chemical and morphological analyzes for all leagues, it was observed that there was dissociation of SiC and Si3N4, as well as diffusion of Si in Ni matrix and carbon cluster and dispersed in the matrix, which also occurred for the alloys with Si carriers and metallic graphite. So the league that was presented better results containing Si Ni with graphite metallic alloy as carriers, since this had dispersed graphite best in the league, reaching the microstructural model proposed, which is necessary for material characteristic of solid lubricant, so how we got the best results when the density and hardness of the alloy

Revestimentos a base de Ta/Al2O3 produzidos por aspersão térmica sobre substrato metálico

Metal substrates were coated by thermal spraying plasma torch, they were positioned at a distance of 4 and 5 cm from the nozzle exit of the plasma jet. The starting materials were used for deposition of tantalum oxide powder and aluminium. These two materials were mixed and ground into high-energy mill, then immersed in the torch for the production of alumina coating infused with particles of tantalum with nano and micrometric size. The spraying equipment used is a plasma torch arc not transferred, which operating in the range of 250 A and 80 V, was able to produce enough heat to ignite aluminothermic between Ta2O5 and aluminum. Upon reaching the plasma jet, the mixing powders react with the heat of the blaze, which provides sufficient energy for melting aluminum particles. This energy is transferred through mechanisms of self-propagating to the oxide, beginning a reduction reaction, which then hits on the surface of the substrate and forms a coating on which a composite is formed by a junction metal - ceramic (Ta +Al2O3). The phases and quantification of each were obtained respectively by X-ray diffraction and the Rietveld method. Morphology by scanning electron microscopy and chemical analysis by energy dispersive spectroscopy EDS. It was also performed measurements of the substrate roughness, Vickers microhardness measurements in sprays and determination of the electron temperature of the plasma jet by optical emission spectroscopy EEO. The results confirmed the expectation generated around the end product of spraying the mixture Ta2O5 + Al, both in the formation of nano-sized particles and in their final form. The electron excitation temperature was consistent with the purpose of work, in addition, the thermodynamic temperature was efficient for the reduction process of Ta2O5. The electron excitation temperature showed values of 3000, 4500 and 8000 K for flows10, 20 and 30 l / min respectively, these values were taken at the nozzle exit of the plasma jet. The thermodynamic temperature around 1200 ° C, was effective in the reduction process of Ta2O5

Obtenção de pós de tântalo metálico a partir da redução aluminotérmica com ignição a plasma

Metallic tantalum has a high commercial value due to intrinsic properties like excellent ductility, corrosion resistance, high melt and boiling points and good electrical and thermal conductivities. Nowadays, it is mostly used in the manufacture of capacitors, due to excellent dielectric properties of its oxides. In the nature, tantalum occurs in the form of oxide and it is extracted mainly from tantalite-columbite ores. The tantalum is usually produced by the reduction of its oxide, using reductants like carbon, silicon, calcium, magnesium and aluminum. Among these techniques, the aluminothermic reduction has been used as the industrial method to produce niobium, tantalum and their alloys, due to the easy removal of the Al and Al2O3 of the system, easing further refining. In conventional aluminothermic reduction an electrical resistance is used to trigger the reaction. This reaction self-propagates for all the volume of material. In this work, we have developed a novel technique of aluminothermic reduction that uses the hydrogen plasma to trigger the reaction. The results obtained by XRD, SEM and EDS show that is possible to obtain a compound rich in tantalum through this technique of aluminothermic reduction in the plasma reactor

Estudo termo-mecânico de interconector metálico recoberto com filme de La0,8Ca0,2CrO3 e de interconector cerâmico de La0,8Sr0,2Cr0,92Co0,08O3 para PaCOS

Doped lanthanum chromite ( LaCrO3 ) has been the most common material used as interconnect in solid oxide fuel cells for high temperature ( SOFC-HT ) that enabling the stack of SOFCs. The reduction of the operating temperature, to around 800 º C, of solid oxide fuel cells enabled the use of metallic interconnects as an alternative to ceramic LaCrO3, From the practical point of view, to be a strong candidate for interconnect the material must have good physical and mechanical properties such as resistance to oxidizing and reducing environments, easy manufacture and appropriate thermo-mechanical properties. Thus, a study on the physic-mechanical interconnects La0,8Sr0,2Cr0,92Co0,08O3 ceramics for SOFC -AT obtained by the method of combustion , as well as thermo-mechanical properties of metallic interconnects (AISI 444) covered with La0,8Ca0,2CrO3 by deposition technique by spray-pyrolysis fuel cells for intermediate temperature (IT-SOFCs). The La0,8Sr0,2Cr0,92Co0,08O3 was characterized by X -ray diffraction(XRD) , density and porosity , Vickers hardness (HV) , the flexural strength at room temperature and 900 °C and scanning electron microscopy (SEM). The X -ray diffraction confirmed the phase formation and LaCrO3 and CoCr2O4, in order 6 GPa hardness and mechanical strength at room temperature was 62 MPa ceramic Interconnector. The coated metal interconnects La0,8Ca0,2CrO3 passed the identification by XRD after deposition of the film after the oxidation test. The oxidative behavior showed increased resistance to oxidation of the metal substrate covered by La0,8Ca0,2CrO3 In flexural strength of the coated metal substrate, it was noticed only in the increased room temperature. The a SEM analysis proved the formation of Cr2O3 and (Cr,Mn)3O4 layers on metal substrate and confirmed the stability of the ceramic La0,8 Ca0,2CrO3 film after oxidative test

Uma aplicação da apredizagem por reforço na otimização da produção em um campo de petróleo

The objective of reservoir engineering is to manage fields of oil production in order to maximize the production of hydrocarbons according to economic and physical restrictions. The deciding of a production strategy is a complex activity involving several variables in the process. Thus, a smart system, which assists in the optimization of the options for developing of the field, is very useful in day-to-day of reservoir engineers. This paper proposes the development of an intelligent system to aid decision making, regarding the optimization of strategies of production in oil fields. The intelligence of this system will be implemented through the use of the technique of reinforcement learning, which is presented as a powerful tool in problems of multi-stage decision. The proposed system will allow the specialist to obtain, in time, a great alternative (or near-optimal) for the development of an oil field known

Eficácia do paration metílico e do extrato aquoso de folhas secas de nim no controle de anacanthorus penilabiatus (monogenoidea) em pacu (piaractus mesopotamicus)

This work determined the efficacy of the insecticide methyl parathion and the natural pesticide azadirachtin present in the aqueous extract of dry neem leaves (AEDNL) to Anacanthorus penilabiatus (Monogenoidea) control in pacu (Piaractus mesopotamicus). The efficacy of methyl parathion was evaluated in an experiment consisting of six treatments (0.0, 3.0, 4.0, 5.0, 6.0 and 7.0 mg methyl parathion/L water) and five exposure times (2, 4, 8, 16 and 24 h). The efficacy of azadirachtin present in AEDNL was assessed in an experiment consisting of seven treatments (0,0; 25; 50; 75; 100; 125; e 150 mL/L water) and five exposure times (24, 48, 72, 96 and 120 h). The efficacy of methyl parathion increased with increasing concentration and exposure time. The highest control efficacy was obtained with a concentration of 7 mg methyl parathion/L at all exposure times. In this treatment, the highest efficacies were observed at 16 and 24 h of exposure, with a control rate of 96.2 and 97.0%, respectively. For the AEDNL, the highest control efficacy (89.2%) was obtained with a concentration of 2.9 mg/L after 120 h of exposure. The efficacy in the treatments employing 1.47 and 1.18 mg/L was 83.9 and 82.5%, respectively, after 120 h of exposure. Methyl parathion presented a higher efficacy in the control of A. penilabiatus than the AEDNL. The AEDNL was moderately effective in the control of the parasite.

Aprendizado por Reforço com Valores deInfluência em Sistemas Multi-Agente

We propose a new paradigm for collective learning in multi-agent systems (MAS) as a solution to the problem in which several agents acting over the same environment must learn how to perform tasks, simultaneously, based on feedbacks given by each one of the other agents. We introduce the proposed paradigm in the form of a reinforcement learning algorithm, nominating it as reinforcement learning with influence values. While learning by rewards, each agent evaluates the relation between the current state and/or action executed at this state (actual believe) together with the reward obtained after all agents that are interacting perform their actions. The reward is a result of the interference of others. The agent considers the opinions of all its colleagues in order to attempt to change the values of its states and/or actions. The idea is that the system, as a whole, must reach an equilibrium, where all agents get satisfied with the obtained results. This means that the values of the state/actions pairs match the reward obtained by each agent. This dynamical way of setting the values for states and/or actions makes this new reinforcement learning paradigm the first to include, naturally, the fact that the presence of other agents in the environment turns it a dynamical model. As a direct result, we implicitly include the internal state, the actions and the rewards obtained by all the other agents in the internal state of each agent. This makes our proposal the first complete solution to the conceptual problem that rises when applying reinforcement learning in multi-agent systems, which is caused by the difference existent between the environment and agent models. With basis on the proposed model, we create the IVQ-learning algorithm that is exhaustive tested in repetitive games with two, three and four agents and in stochastic games that need cooperation and in games that need collaboration. This algorithm shows to be a good option for obtaining solutions that guarantee convergence to the Nash optimum equilibrium in cooperative problems. Experiments performed clear shows that the proposed paradigm is theoretical and experimentally superior to the traditional approaches. Yet, with the creation of this new paradigm the set of reinforcement learning applications in MAS grows up. That is, besides the possibility of applying the algorithm in traditional learning problems in MAS, as for example coordination of tasks in multi-robot systems, it is possible to apply reinforcement learning in problems that are essentially collaborative

Uma implementação paralela híbrida para o problema do caixeiro viajante usando algoritmos genéticos, GRASP e aprendizagem por reforço

The metaheuristics techiniques are known to solve optimization problems classified as NP-complete and are successful in obtaining good quality solutions. They use non-deterministic approaches to generate solutions that are close to the optimal, without the guarantee of finding the global optimum. Motivated by the difficulties in the resolution of these problems, this work proposes the development of parallel hybrid methods using the reinforcement learning, the metaheuristics GRASP and Genetic Algorithms. With the use of these techniques, we aim to contribute to improved efficiency in obtaining efficient solutions. In this case, instead of using the Q-learning algorithm by reinforcement learning, just as a technique for generating the initial solutions of metaheuristics, we use it in a cooperative and competitive approach with the Genetic Algorithm and GRASP, in an parallel implementation. In this context, was possible to verify that the implementations in this study showed satisfactory results, in both strategies, that is, in cooperation and competition between them and the cooperation and competition between groups. In some instances were found the global optimum, in others theses implementations reach close to it. In this sense was an analyze of the performance for this proposed approach was done and it shows a good performance on the requeriments that prove the efficiency and speedup (gain in speed with the parallel processing) of the implementations performed

Uma contribuição à solução do problema dos k-servos usando aprendizagem por reforço

Neste trabalho é proposto um novo algoritmo online para o resolver o Problema dos k-Servos (PKS). O desempenho desta solução é comparado com o de outros algoritmos existentes na literatura, a saber, os algoritmos Harmonic e Work Function, que mostraram ser competitivos, tornando-os parâmetros de comparação significativos. Um algoritmo que apresente desempenho eficiente em relação aos mesmos tende a ser competitivo também, devendo, obviamente, se provar o referido fato. Tal prova, entretanto, foge aos objetivos do presente trabalho. O algoritmo apresentado para a solução do PKS é baseado em técnicas de aprendizagem por reforço. Para tanto, o problema foi modelado como um processo de decisão em múltiplas etapas, ao qual é aplicado o algoritmo Q-Learning, um dos métodos de solução mais populares para o estabelecimento de políticas ótimas neste tipo de problema de decisão. Entretanto, deve-se observar que a dimensão da estrutura de armazenamento utilizada pela aprendizagem por reforço para se obter a política ótima cresce em função do número de estados e de ações, que por sua vez é proporcional ao número n de nós e k de servos. Ao se analisar esse crescimento (matematicamente, ) percebe-se que o mesmo ocorre de maneira exponencial, limitando a aplicação do método a problemas de menor porte, onde o número de nós e de servos é reduzido. Este problema, denominado maldição da dimensionalidade, foi introduzido por Belmann e implica na impossibilidade de execução de um algoritmo para certas instâncias de um problema pelo esgotamento de recursos computacionais para obtenção de sua saída. De modo a evitar que a solução proposta, baseada exclusivamente na aprendizagem por reforço, seja restrita a aplicações de menor porte, propõe-se uma solução alternativa para problemas mais realistas, que envolvam um número maior de nós e de servos. Esta solução alternativa é hierarquizada e utiliza dois métodos de solução do PKS: a aprendizagem por reforço, aplicada a um número reduzido de nós obtidos a partir de um processo de agregação, e um método guloso, aplicado aos subconjuntos de nós resultantes do processo de agregação, onde o critério de escolha do agendamento dos servos é baseado na menor distância ao local de demanda

Classificação de padrões através de um comitê de máquinas aprimorado por aprendizagem por reforço

Reinforcement learning is a machine learning technique that, although finding a large number of applications, maybe is yet to reach its full potential. One of the inadequately tested possibilities is the use of reinforcement learning in combination with other methods for the solution of pattern classification problems. It is well documented in the literature the problems that support vector machine ensembles face in terms of generalization capacity. Algorithms such as Adaboost do not deal appropriately with the imbalances that arise in those situations. Several alternatives have been proposed, with varying degrees of success. This dissertation presents a new approach to building committees of support vector machines. The presented algorithm combines Adaboost algorithm with a layer of reinforcement learning to adjust committee parameters in order to avoid that imbalances on the committee components affect the generalization performance of the final hypothesis. Comparisons were made with ensembles using and not using the reinforcement learning layer, testing benchmark data sets widely known in area of pattern classification

Roteamento em Redes de Sensores Sem Fios Com Base Em Aprendizagem Por Reforço

The use of wireless sensor and actuator networks in industry has been increasing past few years, bringing multiple benefits compared to wired systems, like network flexibility and manageability. Such networks consists of a possibly large number of small and autonomous sensor and actuator devices with wireless communication capabilities. The data collected by sensors are sent directly or through intermediary nodes along the network to a base station called sink node. The data routing in this environment is an essential matter since it is strictly bounded to the energy efficiency, thus the network lifetime. This work investigates the application of a routing technique based on Reinforcement Learning s Q-Learning algorithm to a wireless sensor network by using an NS-2 simulated environment. Several metrics like energy consumption, data packet delivery rates and delays are used to validate de proposal comparing it with another solutions existing in the literature